Vaccine hesitancy prospectively predicts nocebo side-effects following COVID-19 vaccination

The directionality between vaccine hesitancy and COVID-19 vaccine side-effects has not been hitherto examined. We hypothesized a nocebo effect, whereby vaccine hesitancy towards the second Pfizer vaccination dose predicts subsequent side-effects for a booster dose, beyond other effects. We expected these nocebo effects to be driven by (mis)information in males and prior experience in females. A representative sample of older adults (n = 756, mean age = 68.9 ± 3.43) were questioned in a typical cross-lagged design (wave 1 following a second Pfizer dose, wave 2 after their booster). As hypothesized, earlier vaccine hesitancy predicted subsequent booster side-effects for females (β = 0.10 p = 0.025, f 2 = 0.02) and males (β = 0.34, p < 0.001, f 2 = 0.16); effects were stronger in males (χ2Δ (1) = 4.34, p = 0.03). The (W1-to-W2) side-effect autoregression was stronger in females (β = .34, p < 0.001; males β = 0.18, p < 0.001), χ2Δ (1) = 26.86, p < 0.001. Results show that a quantifiable and meaningful portion of COVID-19 vaccine side-effects is predicted by vaccine hesitancy, demonstrating that side-effects comprise a psychosomatic nocebo component in vaccinated individuals. The data reveal distinct risk levels for future side-effects, suggesting the need to tailor public health messaging.


Vaccine hesitancy
The eight vaccine-hesitancy items were adapted from the Giambi et al. [1] vaccine hesitancy questionnaire and were used in prior COVID-19 studies [2]. This questionnaire included the following 8 items. 1) I am concerned about immediate negative vaccine sideeffects; 2) I am concerned about long-term damage due to the vaccine; 3) The Covid-19 vaccine may be more dangerous than COVID-19 itself; 4) The need to vaccinate is driven by economic interests of the pharmaceutical companies; 5) The health authorities are exposing us to positive information about the vaccine but not its dangers; 6) Vaccination is not necessary, provided you live a healthy life and follow the health regulations concerning corona; 7) Vaccination is not necessary, since COVID-19 is not as dangerous as people say it is; 8) The vaccine will impair our immune system or cause an overload.

Side-effect severity
The percentages of endorsing each severity rating for each of the 21 side-effects, at each wave are depicted in Table S2. In order to render these results comparable to studies that used a dichotomized measure of severity, we also present the frequencies of two dichotomized scores. The first dichotomized score (first column in table) was computed by collapsing percentages across severity ratings in the following manner: persons endorsing the severity level "none" and "a-little" (levels 1 and 2) were grouped together as not having suffered, vs. all other levels (from levels 3-moderate to 5-very severe). The second dichotomized score was more liberal at estimating side-effects, as it divided those who did not experience side-effects at all (rating of 1-none) vs. all other severity levels (ratings 2-a little -5-very severely). See first two columns in Table S2.

Additional Analyses
The additional analyses focused on three issues. The first goal was to further analyze sub-groups of side-effects to discern if the current findings were specific to certain side-effect clusters. The primary division of side-effects was based on earlier research which showed that psychological factors predicted a narrow list of seven side-effects [3], out of which, three side-effects were observed in the Pfizer trials [4]. Accordingly, the data were re-analyzed to examine if vaccine hesitancy predicting side-effects would hold across different side-effects (See Tables S3 and S4). The second goal was to assess if the effect of vaccine hesitancy predicting side-effects would hold beyond different vaccine hesitancy items, i.e., even vaccine hesitancy items that do not tap expectations of side-effects.
Showing that results hold even beyond these expectations items would suggest that results are not stemming from domain overlap, i.e., that the vaccine hesitancy items tapping side-effects are driving the prediction of actual side-effects, please see Table S5. We also addressed in a separate analysis only the (three) vaccine hesitancy expectation items (see Table S6). The third goal was to address if this effect would hold when general anxiety disorder symptoms (GAD-7) and a single W2 item measuring vaccine expectation, were added (see Table S7).

1.Side-effect division
The 7 side-effects used in a previous study [3] were 1) pain at injection site, 2) fever, 3) chills, 4) headache, 5) joint pain, 6) nausea, and 7) fatigue. Three of these side-effects (pain at injection site, headaches and fatigue) were selected due to their importance in clinical trials [4] and appear on the CDC site [5]. We added weakness as another side-effect related to the first group of side-effects, yielding 8 side-effects (this did not change results). The results appear in Table S3, which show that the W1-to W2 cross hesitancy effect was even slightly stronger for the non-typical side-effects (.20 vs. .15, See Table S3).

Additional analyses addressing vaccine hesitancy items
These supplementary findings are similar to the results depicted in the text, i.e., this was true across the different groupings of sideeffects. Namely, only hesitancy predicted subsequent side-effects but not the reverse. Similar results were obtained when the model was run on each of the five factors (obtained after running a factor analysis on side-effects). The aim of the next analyses was to examine if results also remain the same when removing vaccine hesitancy items related to side-effects. This analysis was performed twice, once after removal of items that even indirectly pertained to expectations that the vaccine is harmful (items 1,2,3,5 & 8, Table  S5, top), and again a second time, after removing only three items directly pertaining to negative expectations of vaccination sideeffects (Table S5, Table S5, the expected results were obtained.  (without items, 1,2, 3, 5, and 8 (2) Multi-Gender group analysis (male/female) Side-effects (lagged effect) .21*** / .35*** Hesitancy to Side-effects. 23*** /.08 p = .091 Hesitancy (lagged effect) .48***/.52*** Side-effects to Hesitancy -.04 p=.424 /-.01 p=.863 *p<.01, **p<.001***p<.0001, p value depicted when not significant.

bottom). As shown in
As indicated, our goal (Table S5) was to examine if vaccine hesitancy prospectively predicts side-effects. We also wanted to show that it was not the component of negative expectation (regarding side-effects) which was driving the link between vaccine hesitancy and actual side-effects. Had this above analysis not been conducted, it could have been claimed that the linking of vaccine hesitancy (which includes expectations of side-effects) with actual side-effects, stems from the domain overlap, as both variables are tapping aspects of side-effects. In summary, the results of the main model reported in the text were reliable across side-effects and across vaccine hesitancy items, namely, for all cases, vaccine-hesitancy predicted subsequent side-effects across different vaccine hesitancy items and different side-effects; the opposite direction was not obtained in any scenario.

Expectation and Anxiety
One final issue is that Nocebo effects may typically be impacted by one's expectations [6] and one's negative affect [7]. As mentioned in the limitations (see Discussion), we did not measure expectations of specific outcomes, as typically computed. Thus, in the next analysis we addressed only the three vaccine hesitancy items that tap general negative expectations to asses if results would remain the same. These data appear in Table S6, and show the same result pattern. Only the direction of vaccine hesitancy predicting side-effects was significant, but not the opposite direction. We employed a final model that includes both general anxiety disorder symptoms (GAD-7) assessed at both waves, to examine for example if it predicts side-effects. We also measured a single item at W2 that assess one's general expectation "that the vaccine will  (2) Multi-Gender group analysis (male/female) Side-effects (lagged effect) .18** / .33*** Hesitancy to Side-effects. 38*** /.12* Hesitancy (lagged effect) .52***/.48*** Side-effects to Hesitancy .03 p=.538 /.07 p=.107 protect me from COVID-19". This item was rated on a 5-point Likert scale 1-not at all to 5-very much). We entered this item in the final analysis as a dependent variable to be predicted by W1 variables (e.g., if expectation is predicted by anxiety). effects at W1 did not predict one's expectation (that the vaccine will protect me from COVID-19), however more hesitancy at W1 predicted lower levels of this expectation. The results were also similar in the multigroup model.
In conclusion, the supplementary results indicate that the data reported in the main text were reliable both across different groupings of side-effects and different groupings of vaccine hesitancy items (expectancy items vs. non-expectancy items). These results held even when anxiety was entered into the model. In all cases, vaccine hesitancy predicted future side-effects, beyond other effects, such as one's previous experience reflected by W1 side-effects. The opposite direction of W1 side-effects predicting W2 vaccine hesitancy was not significant in any scenario.